Bottom-up development of passenger travel demand scenarios in Japan considering heterogeneous actors and reflecting a narrative of future socioeconomic change

Train stop planning provides appropriate service for travel demand and stations and plays a significant role in railway operation. This paper formulates stop planning from the point of view of direct travel between origin-destination (O-D) stations and proposes an analytical method to theoretically derive optimal service frequencies for O-D demand on different levels. Considering different O-D demand characteristics and train service types, we introduce the concept of stop probability to present the mathematical formulation for stop planning with the objective of minimizing per capita travel time, which is solved by an iterative algorithm combined with local search. The resulting optimal stop probabilities can be used to calculate the required service frequency for each train type serving different demand categories. Numerical examples, based on three real-life high-speed railway lines, demonstrate the validity of the proposed method. The proposed approach provides a more flexible and practical way for stop planning that explicitly takes into account the importance of different stations and passenger travel characteristics.

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Long Term Forecasting of International Air Travel Demand in Nigeria (2018-2028)

American International Journal of Multidisciplinary Scientific Research ◽

10.46281/aijmsr.v1i2.184 ◽

2018 ◽

Vol 1 (2) ◽

pp. 16-24

Author(s):

Adeniran, Adetayo Olaniyi ◽

Kanyio, Olufunto Adedotun

Keyword(s):

Travel Demand ◽

Air Travel ◽

Least Square ◽

Coefficient Of Determination ◽

High Tendency ◽

Passenger Travel ◽

Percent Increase ◽

Air Travel Demand ◽

Long Term Forecasting

This study examines long term forecasting of international air travel demand in Nigeria. Yearly data from 2001 to 2017 were collected from secondary sources. Ordinary Least Square (OLS) regression was used to forecast the ten years (2018 to 2028) demand for international air passenger travel in Nigeria. The demand for international air passenger in Nigeria from year 2001 to 2017 was compared with the forecast. Calculation reveals that the coefficient of determination R2 is 0.815, while the computed reveals that the coefficient of determination R2 is 0.769, this difference can be attributed to approximations to two decimal places for calculated test. The calculated test and computed test reveals that the error term is minimal and the explanation level is high; hence the prediction or forecast is reliable. The forecast for years 2020, 2025 and 2028 are 5,282,453, 6,342,519, and 6,978,559 respectively which are about 48 percent increase, 78 percent increase, and 95 percent increase respectively from demand in year 2017. The forecast of ten years from year 2018 to year 2028 reveals that there will be more increase in the demand for international air passenger travel in Nigeria. The implication of this increment is that existing air transport infrastructures should be upgraded, and new infrastructures should be procured and installed; airport and airline operations should be reviewed and strategized such that they will meet the expectations of airline and airport users. Other concerned business stakeholders should use this data to plan and invest as there is high tendency for profit making.

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Forecasting passenger travel demand for air and high-speed rail integration service: A case study of Beijing-Guangzhou corridor, China

Transportation Research Part A Policy and Practice ◽

10.1016/j.tra.2016.10.002 ◽

2016 ◽

Vol 94 ◽

pp. 397-410 ◽

Cited By ~ 24

Author(s):

Zhi-Chun Li ◽

Dian Sheng

Keyword(s):

High Speed ◽

Travel Demand ◽

High Speed Rail ◽

Passenger Travel ◽

Integration Service

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Integration of National Long-Distance Passenger Travel Demand Model with Tennessee Statewide Model and Calibration to Big Data

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2653-09 ◽

2017 ◽

Vol 2653 (1) ◽

pp. 75-81 ◽

Cited By ~ 3

Author(s):

Vincent L. Bernardin ◽

Nazneen Ferdous ◽

Hadi Sadrsadat ◽

Steven Trevino ◽

Chin-Cheng Chen

Keyword(s):

Big Data ◽

Travel Demand ◽

Data Sources ◽

Demand Model ◽

Long Distance ◽

Passenger Travel ◽

Distance Model ◽

National Model ◽

Distance Travel ◽

Long Distance Travel

The Tennessee Department of Transportation replaced the quick-response-based long-distance component in its statewide model by integrating the new national long-distance passenger travel demand model in a new statewide model and calibrating it to long-distance trips observed in cell phone origin–destination data. The national long-distance model is a tour-based simulation model developed from FHWA research on long-distance travel behavior and patterns. The tool allows the evaluation of many policy scenarios, including fare or service changes for various modes, such as commercial air, intercity bus, Amtrak rail, and highway travel. The availability of this tool presents an opportunity for state departments of transportation in developing statewide models. Commercial big data from cell phones for long-distance trips also pre-sents an opportunity and a new data source for long-distance travel patterns, which previously have been the subject of limited data collection, in the form of surveys. This project is the first to seize on both of these opportunities by integrating the national long-distance model with the new Tennessee statewide model and by processing big data for use as a calibration target for long-distance travel in a statewide model. The paper demonstrates the feasibility of integrating the national model with statewide models, the ability of the national model to be calibrated to new data sources, the ability to combine multiple big data sources, and the value of big data on long-distance travel, as well as important lessons on its expansion.

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Person-Based Micro-Simulation Demand Model for National Long-Distance Travel in the U.S.A.

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120919119 ◽

2020 ◽

Vol 2674 (6) ◽

pp. 297-309

Author(s):

Lei Zhang ◽

Yijing Lu ◽

Sepehr Ghader ◽

Carlos Carrion ◽

Arash Asadabadi ◽

...

Keyword(s):

Large Scale ◽

Travel Demand ◽

Demand Model ◽

Long Distance ◽

Fuel Price ◽

Travel Survey ◽

Passenger Travel ◽

Micro Simulation ◽

Distance Travel ◽

Long Distance Travel

As the nation and various states engage in funding transportation infrastructure improvements to meet future long-distance passenger travel demand, it is imperative to develop effective and practical modeling methods for analysis of long-distance passenger travel. Evaluating national-level infrastructure improvements requires a reliable analysis tool to model the demand for long-distance travel. The national travel demand model presented in this paper implements a person-level tour-based micro-simulation approach for modeling individuals’ long-distance or national activities in the U.S.A. This paper reviews the model framework, explains the model calibration, and presents applications of the model for policy evaluation and demand prediction. The model was estimated using the latest long-distance travel survey in the U.S.A., which is the 1995 American Travel Survey. As the estimation data is old, and no new long-distance travel survey with appropriate sample size is available to re-estimate the model, model calibration is the solution used to update the model and make it capable of capturing up-to-date travel patterns. Calibrating such a large-scale model can be challenging, because each calibration iteration is very costly. This paper describes the calibration effort conducted on the national long-distance micro-simulation model to showcase how a large-scale travel demand model can be calibrated efficiently. A fuel price scenario is analyzed to show how the national travel demand will change under a national fuel price increase scenario in the future year 2040. Another scenario analysis corresponding to construction of high-speed rail (HSR) is conducted to observe the effects of adding a HSR system to the northeast corridor on travel demand from a national perspective.

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